Biogen
Research Fellow, Machine Learning, Small Molecule Drug Design
Cambridge, MA
Sep 25, 2024
fulltime
Full Job Description

Job Description

About This Role

The computational science group at Biogen are seeking a creative and self-motivated research fellow to design, develop, and apply new machine learning algorithms for small molecule drug discovery. The Research Fellow role at Biogen is an 18-month position designed to provide a unique opportunity for scientists to gain exposure to drug discovery and development and train in an industry research setting. In this role, you will collaborate across medicinal chemistry to leverage machine learning algorithms for small molecule drug discovery.

What You'll Do

  • You will join the growing AI/ML group within computational science as a research fellow and participate in cutting-edge research in machine learning and its applications to small molecule drug discovery and design
  • You will collaborate closely with cross-functional teams across medicinal chemistry to solve complex problems including molecular generation, property optimization, and synthesis accessibility
  • You will drive publications in scientific journals and machine learning conferences, and present results at internal and external meetings

Qualifications

Who You Are

You are a recent PhD graduate with strong self-motivation and eager to make impactful contributions to drug discovery. You will be expected to stay current with the machine learning literature and apply the latest advances to address drug discovery project challenges.

Required Skills/Education

  • Ph.D. in computer science or computational science field
  • 0-2 years of postdoctoral experience
  • Extensive experience in one of AI/ML fields, such as Large Language Models, Deep Generative Models, Geometric Deep Learning, and related areas
  • Proficiency in Python and at least one ML frameworks (PyTorch / TensorFlow)
  • Extensive hands-on coding and actively contribute to platform development
  • Track record of publications, and/or scientific presentations
  • Should be able to work in a multidisciplinary team
  • Excellent oral and written communication skills

Preferred Skills

  • Hands-on experience in implementing deep learning models (e.g. Transformers, GNNs, RL)
  • Experience in solving real-world problems using deep learning in a multidisciplinary setting is a strong plus
  • Strong research interest in drug discovery
  • Experience with cheminformatics toolkits (RDKit/Schrodinger suite, etc) is a desirable

Additional Information

Why Biogen?

We are a global team with a commitment to excellence, and a pioneering spirit. As a mid-sized biotechnology company, we provide the stability and resources of a well-established business while fostering an environment where individual contributions make a significant impact. Our team encompasses some of the most talented and passionate achievers who have unparalleled opportunities for learning, growth, and expanding their skills. Above all, we work together to deliver life-changing medicines, with every role playing a vital part in our mission. Caring Deeply. Achieving Excellence. Changing Lives.

At Biogen, we are committed to building on our culture of inclusion and belonging that reflects the communities where we operate and the patients we serve. We know that diverse backgrounds, cultures, and perspectives make us a stronger and more innovative company, and we are focused on building teams where every employee feels empowered and inspired. Read on to learn more about our DE&I efforts.

All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, sexual orientation, marital status, race, color, national origin, ancestry, ethnicity, religion, age, veteran status, disability, genetic information or any other basis protected by federal, state or local law. Biogen is an E-Verify Employer in the United States.

 

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Job Information
Job Category:
Science
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Research Fellow, Machine Learning, Small Molecule Drug Design
Biogen
Cambridge, MA
Sep 25, 2024
fulltime
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